translational-bioinformatics

End-to-end pipeline for cancer biomarker discovery on synthetic TCGA-like data. Rigorous DE (log2FC + Welch t-test + BH-FDR), leakage-safe ML with nested CV, recovery metrics, and CI on Python 3.10–3.12.

TCGA-OV multi-omics network analysis pipeline with compliant JBI manuscript bundle, external ovarian validation, and public derived-result releases

Contains assignments from the BF528 course, focusing on applications in translational bioinformatics, including end-to-end analyses of various omics data and bioinformatics workflows using tools like Snakemake.

An end-to-end translational transcriptomics pipeline integrating TCGA and GTEx V10 cohorts to stratify mixed-phenotype Renal Cell Carcinoma (RCC) and evaluate candidate biomarker target-safety windows for drug discovery.

TargetIntel-IO is an explainable, rule-based tool that ranks and classifies candidate targets in anti-PD-1-resistant melanoma by therapeutic intent: antibody/IO-combination, biomarker, or small-molecule strategy, with evidence-based reasoning and benchmark-checked accuracy behind every call.